BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Whole Genome Association Study:  What can be learned from a large 
 clinical cohort? - Professor Sven Bergmann\, Department of Medical Genetic
 s\, University of Lausanne\, Switzerland
DTSTART:20090804T110000Z
DTEND:20090804T120000Z
UID:TALK19322@talks.cam.ac.uk
CONTACT:M. Madan Babu
DESCRIPTION:The Cohorte Lausannoise (CoLaus) is a random population sample
  of more than 6'000 individuals who were genotyped using Affymetrix 500k S
 NP-arrays and for whom a large number of clinically relevant parameters ha
 ve been measured.\n\nAbout 1/3 of the CoLaus individuals had grandparents 
 who immigrated to Switzerland -  mainly from other European countries. Thi
 s allowed for comparing the country of origin of these individual with the
  projection of their genotypic profile onto the principal  components of t
 he entire genotypic dataset. We found an astonishingly close correspondenc
 e between genetic and geographic distances\; indeed\, a geographical map o
 f Europe arises naturally as an efficient two-dimensional summary of genet
 ic variation in Europeans.\n\nNext I will present results from several who
 le-genome association studies that employed CoLaus data that included heig
 ht\, body-mass-index\, serum lipid concentrations and blood pressure as ph
 enotypes\, and used classical scans testing one SNP at a time. These studi
 es (like many others) elucidated many loci with highly significant associa
 tions\, which are promising candidates towards unraveling mechanisms of ac
 tions. Yet\, together these variants only explain a small fraction of the 
 phenotypic variance\, indicating that we still miss a comprehensive pictur
 e of: (a) what are the causal variants\, (b) what effects are attributed b
 y rare variants and/or copy number variations\, (c) what fraction of the v
 ariance can be explained by SNP-SNP or SNP-environment interactions\, and 
 (d) what are the intrinsic limitations of currently used algorithms in dea
 ling with very large sets of genotypic and phenotypic data\, which are par
 tially incomplete or noisy.\n\nI will conclude by outlining our research d
 ealing with these challenges.\n
LOCATION:Structural Studies Seminar Room\, MRC Laboratory of Molecular Bio
 logy\, Cambridge\, UK
END:VEVENT
END:VCALENDAR
